Showing papers by "Benjamin Meder published in 2013"

A blood based 12-miRNA signature of Alzheimer disease patients

Abstract: Alzheimer disease (AD) is the most common form of dementia but the identification of reliable, early and non-invasive biomarkers remains a major challenge. We present a novel miRNA-based signature for detecting AD from blood samples. We apply next-generation sequencing to miRNAs from blood samples of 48 AD patients and 22 unaffected controls, yielding a total of 140 unique mature miRNAs with significantly changed expression levels. Of these, 82 have higher and 58 have lower abundance in AD patient samples. We selected a panel of 12 miRNAs for an RT-qPCR analysis on a larger cohort of 202 samples, comprising not only AD patients and healthy controls but also patients with other CNS illnesses. These included mild cognitive impairment, which is assumed to represent a transitional period before the development of AD, as well as multiple sclerosis, Parkinson disease, major depression, bipolar disorder and schizophrenia. miRNA target enrichment analysis of the selected 12 miRNAs indicates an involvement of miRNAs in nervous system development, neuron projection, neuron projection development and neuron projection morphogenesis. Using this 12-miRNA signature, we differentiate between AD and controls with an accuracy of 93%, a specificity of 95% and a sensitivity of 92%. The differentiation of AD from other neurological diseases is possible with accuracies between 74% and 78%. The differentiation of the other CNS disorders from controls yields even higher accuracies. The data indicate that deregulated miRNAs in blood might be used as biomarkers in the diagnosis of AD or other neurological diseases.

Alterations in cardiac DNA methylation in human dilated cardiomyopathy

Abstract: Dilated cardiomyopathies (DCM) show remarkable variability in their age of onset, phenotypic presentation, and clinical course. Hence, disease mechanisms must exist that modify the occurrence and progression of DCM, either by genetic or epigenetic factors that may interact with environmental stimuli. In the present study, we examined genome-wide cardiac DNA methylation in patients with idiopathic DCM and controls. We detected methylation differences in pathways related to heart disease, but also in genes with yet unknown function in DCM or heart failure, namely Lymphocyte antigen 75 (LY75), Tyrosine kinase-type cell surface receptor HER3 (ERBB3), Homeobox B13 (HOXB13) and Adenosine receptor A2A (ADORA2A). Mass-spectrometric analysis and bisulphite-sequencing enabled confirmation of the observed DNA methylation changes in independent cohorts. Aberrant DNA methylation in DCM patients was associated with significant changes in LY75 and ADORA2A mRNA expression, but not in ERBB3 and HOXB13. In vivo studies of orthologous ly75 and adora2a in zebrafish demonstrate a functional role of these genes in adaptive or maladaptive pathways in heart failure.

Multivariate miRNA signatures as biomarkers for non-ischaemic systolic heart failure

Abstract: Aims Non-ischaemic heart failure is one of the today's most prevalent cardiovascular disorders. Since modern pharmacotherapy has proved to be very effective in delaying disease progression and preventing death, imaging modalities and molecular biomarkers play an important role in early identification and clinical management as well as risk assessment of patients. The present study evaluated for the first time whole peripheral blood miRNAs as novel biomarker candidates for non-ischaemic heart failure with reduced ejection fraction (HF-REF). Methods and results We assessed genome-wide miRNA expression profiles in 53 HF-REF patients and 39 controls. We could identify and validate several miRNAs that show altered expression levels in non-ischaemic HF-REF, discriminating cases from controls both as single markers or when combined in a multivariate signature. In addition, we demonstrate that the miRNAs of this signature significantly correlate with disease severity as indicated by left ventricular ejection fraction. Conclusion Our data further denote that miRNAs are potential biomarkers for systolic heart failure. Since their detection levels in whole blood are also related to the degree of left ventricular dysfunction, they may serve as objective molecular tools to assess disease severity and prognosis.

Refining Diagnostic MicroRNA Signatures by Whole-miRNome Kinetic Analysis in Acute Myocardial Infarction

Abstract: BACKGROUND: Alterations in microRNA (miRNA) expression patterns in whole blood may be useful biomarkers of diverse cardiovascular disorders. We previously reported that miRNAs are significantly dysregulated in acute myocardial infarction (AMI) and applied machine-learning techniques to define miRNA subsets with high diagnostic power for AMI diagnosis. However, the kinetics of the time-dependent sensitivity of these novel miRNA biomarkers remained unknown. METHODS: To characterize temporal changes in the expressed human miRNAs (miRNome), we performed here the first whole-genome miRNA kinetic study in AMI patients. We measured miRNA expression levels at multiple time points (0, 2, 4, 12, 24 h after initial presentation) in patients with acute ST-elevation myocardial infarction by using microfluidic primer extension arrays and quantitative real-time PCR. As a prerequisite, all patients enrolled had to have cardiac troponin T concentrations <50 ng/L on admission as measured with a high-sensitivity assay. RESULTS: We found a subset of miRNAs to be significantly dysregulated both at initial presentation and during the course of AMI. Additionally, we identified novel miRNAs that are dysregulated early during myocardial infarction, such as miR-1915 and miR-181c*. CONCLUSIONS: The present proof-of-concept study provides novel insights into the dynamic changes of the human miRNome during AMI.

Next-Generation Sequencing: From Understanding Biology to Personalized Medicine

Abstract: Within just a few years, the new methods for high-throughput next-generation sequencing have generated completely novel insights into the heritability and pathophysiology of human disease In this review, we wish to highlight the benefits of the current state-of-the-art sequencing technologies for genetic and epigenetic research We illustrate how these technologies help to constantly improve our understanding of genetic mechanisms in biological systems and summarize the progress made so far This can be exemplified by the case of heritable heart muscle diseases, so-called cardiomyopathies Here, next-generation sequencing is able to identify novel disease genes, and first clinical applications demonstrate the successful translation of this technology into personalized patient care

Paleoproteomic study of the Iceman's brain tissue.

Abstract: The Tyrolean Iceman, a Copper-age ice mummy, is one of the best-studied human individuals. While the genome of the Iceman has largely been decoded, tissue-specific proteomes have not yet been investigated. We studied the proteome of two distinct brain samples using gel-based and liquid chromatography–mass spectrometry-based proteomics technologies together with a multiple-databases and -search algorithms-driven data-analysis approach. Thereby, we identified a total of 502 different proteins. Of these, 41 proteins are known to be highly abundant in brain tissue and 9 are even specifically expressed in the brain. Furthermore, we found 10 proteins related to blood and coagulation. An enrichment analysis revealed a significant accumulation of proteins related to stress response and wound healing. Together with atomic force microscope scans, indicating clustered blood cells, our data reopens former discussions about a possible injury of the Iceman’s head near the site where the tissue samples have been extracted.

Fast data-driven calibration of a cardiac electrophysiology model from images and ECG.

Abstract: Recent advances in computational electrophysiology (EP) models make them attractive for clinical use. We propose a novel data-driven approach to calibrate an EP model from standard 12-lead electrocardiograms (ECG), which are in contrast to invasive or dense body surface measurements widely available in clinical routine. With focus on cardiac depolarization, we first propose an efficient forward model of ECG by coupling a mono-domain, Lattice-Boltzmann model of cardiac EP to a boundary element formulation of body surface potentials. We then estimate a polynomial regression to predict myocardium, left ventricle and right ventricle endocardium electrical diffusion from QRS duration and ECG electrical axis. Training was performed on 4,200 ECG simulations, calculated in ≈3s each, using different diffusion parameters on 13 patient geometries. This allowed quantifying diffusion uncertainty for given ECG parameters due to the ill-posed nature of the ECG problem. We show that our method is able to predict myocardium diffusion within the uncertainty range, yielding a prediction error of less than 5ms for QRS duration and 2° for electrical axis. Prediction results compared favorably with those obtained with a standard optimization procedure, while being 60 times faster. Our data-driven model can thus constitute an efficient preliminary step prior to more refined EP personalization.

From medical images to fast computational models of heart electromechanics: an integrated framework towards clinical use

Abstract: With the recent advances in computational power, realistic modeling of heart function within a clinical environment has come into reach Yet, current modeling frameworks either lack overall completeness or computational performance, and their integration with clinical imaging and data is still tedious In this paper, we propose an integrated framework to model heart electromechanics from clinical and imaging data, which is fast enough to be embedded in a clinical setting More precisely, we introduce data-driven techniques for cardiac anatomy estimation and couple them with an efficient GPU (graphics processing unit) implementation of the orthotropic Holzapfel-Ogden model of myocardium tissue, a GPU implementation of a mono-domain electrophysiology model based on the Lattice-Boltzmann method, and a novel method to correctly capture motion during isovolumetric phases Benchmark experiments conducted on patient data showed that the computation of a whole heart cycle including electrophysiology and biomechanics with mesh resolutions of around 70k elements takes on average 1min 10s on a standard desktop machine (Intel Xeon 24GHz, NVIDIA GeForce GTX 580) We were able to compute electrophysiology up to 405× faster and biomechanics up to 152× faster than with prior CPU-based approaches, which breaks ground towards model-based therapy planning

Complex sets of mirnas as non-invasive biomarkers for early diagnosis of acute myocardial infarction

Abstract: The present invention relates to non-invasive methods for early diagnosis and/or differential diagnosis of acute myocardial infarction in a blood sample of a subject by determining the level of at least one miRNA selected from hsa-miR-7-1*, hsa-miR-566, hsa-miR-455-3p, hsa-miR-1254, hsa-miR-380*, hsa-miR-636, hsa-miR-1291, hsa- miR-181c* and hsa-miR-1915. Further, the present invention relates to polynucleotides or sets of polynucleotides for detecting miRNAs or sets of miRNAs for early diagnosis and/or differential diagnosis of acute myocardial infarction in a blood sample of a subject.

Epigenetic signatures as marker for cardiomyopathies and myocardial insufficiencies

Abstract: The present invention relates to the use of DNA methylation profiles of patient samples for the diagnosis, prognosis and/or therapy monitoring of a heart disease in a patient, wherein the DNA methylation profile of the patient sample is compared with the DNA methylation profile of a control sample, and wherein a difference in the DNA methylation profile of the patient sample compared to the control sample is indicative of a heart disease or of the risk for developing a heart disease or for a prediction of therapy effects or therapy outcome. The present invention further relates to methods for the diagnosis, prognosis and/or therapy monitoring of a heart disease in a patient, comprising determining the DNA methylation profile in a patient sample comprising genomic DNA from heart cells, heart tissue or peripheral blood; and comparing the DNA methylation profile in the patient sample with the DNA methylation profile from a normal subject not having a heart disease or having a normal heart function. The present invention furthermore relates to kits that are suitable for the methods and uses of the invention. The present invention furthermore relates to the use of ADORA2A, ERBB3, LY75, HOXB13, GF11, CLDN4, FDX1, ID4, NAT1, PPARGC1A, SULF2, TFF1, TKT, ATP2C, CCDC59, GSTM5m, SLC9A6 and TDG as marker for the diagnosis, prognosis and/or therapy monitoring of a heart disease in a patient.